1. Field of the Invention
The present disclosure relates generally to a method for controlling temperature. More particularly, the invention relates to an adaptive feed forward method for PID temperature control in the context of a smoker controller. The inventive method improves temperature control performance by adjusting feed forward parameters depending on smoker controller output and process response over time.
2. Description of the Related Art
A PID controller, also known as a proportional-integral-derivative controller, provides a versatile feedback compensator structure that improves system performance. A PID controller is a control loop feedback mechanism commonly used in industrial control systems. A PID controller continuously calculates an error value as the difference between a measured process variable and a desired set point. A PID controller responds to error signals and attempts to correct errors where the system over or undershoots a set point. Thus, the controller attempts to minimize the error over time by adjustment of a control variable. The set point is where you would like the measurement to be. Error is defined as the difference between set point and measurement.Error=Set Point−Measurement
The variable being adjusted is called the manipulated variable, which usually is equal to the output of the controller. Thus, the output of PID controllers will change in response to a change in measurement or set point.
PID controllers are designed to eliminate the need for continuous operator attention. For instance, cruise control in a car and a house thermostat are common examples of how controllers are used to automatically adjust some variable to hold the measurement (or process variable) at the set point.
In a closed loop system, the tracking error is the difference between the desired input value and the actual output value. Typically, the value of the tracking error will be sent to the PID controller, and the controller computes both the derivative and the integral of the tracking error. The control signal is equal to the proportional gain multiplied by the tracking error plus the integral gain multiplied by the integral of the error plus the derivative gain multiplied by the derivative of the error.
A proportional controller will have the effect of reducing the rise time and will reduce but never eliminate the steady state error.
An integral controller will have the effect of eliminating the steady-state error for a constant or step input, but it may make the transient response slower.
A derivative controller will have the effect of increasing the stability of the system, reducing the overshoot, and improving the transient response.
The proportional, integral and derivative parameters of a PID controller can be modified or tuned to deal with specific process requirements.
In the framework of a PID controller, P (proportional gain) accounts for the present values of the error. That is the variance between the set point and the current process temperature. For example, if the error is large and positive the control variable will be large and negative). I (integral gain) accounts for past values of the error. That is, the previous variance from the set point. For example, if the output is not sufficient to reduce the size of the error, the control variable will accumulate over time, causing the controller to apply a stronger action. D (derivative gain) accounts for possible future values of the error, based on its current rate of change. That is, the predicted future variance based on previous and current variance.
Adaptive control is the method used by a controller that adapts to a controlled system with parameters that vary, or are initially uncertain.
It is noted that the temperature indicated on the controller display is only the temperature measured by the temperature sensor and may not be a true indication of the actual temperature. In the context of temperature control, having an accurate temperature measurement and the ability to maintain a constant temperature whether using a barbecue, a batch oven or continuous oven is key to successful and quality temperature control.
Thus, process and temperature controllers provide useful tools to maintain the actual temperature at a set point despite disturbances that may vary the temperature from the ideal set point. Process and temperature controllers are powerful process control tools that take a signal from a temperature device, such as a thermocouple or other sensor and maintain a set point using an output signal.
It is known to control temperature using an adjustment input. U.S. Pat. No. 5,099,442 to Furuta et al. discloses a temperature control apparatus of a learning type for a furnace that runs repetitively with a certain operating pattern of temperature change with time. The apparatus has a dual system model with respect to an enlarged system consisting of the furnace and its controller. For each cycle of the repetition of the certain operating pattern, adjustment input is calculated by using the dual system model and the error between the preset temperature values for the pattern and the actual inside temperatures of the furnace which adjustment input is applied to the enlarged system to cause the inside temperatures to track the preset temperature values. After each cycle of operation, the adjustment input is renewed using the latest value of the above error.
U.S. Pat. No. 4,193,320 (to Sato et al.) teaches a system and method for the adaptive control of a process in which a feed forward control signal corresponding to a process demand is calculated according to a predetermined algebraic function, while a feedback correction signal is calculated on the basis of an error of a process feedback signal indicative of an error of a controlled variable from a predetermined setting, and the controlled variable of the process is controlled on the basis of the sum of these two signals. The adaptive control is such that, when a set point of the function deviates from the actual process demand, a value corresponding to the error appears in the feedback correction signal, and this value is used for automatically modifying the function itself to ensure the adaptive control of the process. A determination is made whether or not the process is in the steady state and when steady state operation is determined, the function of the feed forward control signal is modified.
In the context of a smoker controller, it is desirable to achieve precise temperature control. Thus it is desirable to implement an improved temperature control method using an improved adaptive feed-forward method with a PID temperature controller for regulating temperature control.